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Innovation boot camp

JANUARY - APRIL 2017

From January-April, we partnered with MEDIC (The Medical Innovators Collaborative) to offer a 3 month Innovation Boot Camp in which participants worked as teams to create innovative solutions to real global health problems.

The Innovation Boot Camp was a learning experience in which participants asked questions, learned by doing, and received mentorship and guidance from MEDIC staff and subject matter experts.

The Boot Camp experience culminated in team presentations at SwitchPoint. We were so impressed and inspired by the hard work and innovation of our teams!

What

Innovation Boot Camp sponsored by MEDIC and the Triangle Global Health Consortium

Who

Anyone interested in addressing global health challenges

When

January-April 2017

Timeline

January 27

Kickoff at Triangle Global Health Career Day

January 27-February 7 (9:00am)

Participant Sign-Up Open

Interested students and professionals can sign-up to participate in the Boot Camp. MEDIC will then assemble teams.

February 21

Ideation

Teams will meet with MEDIC to brainstorm and to develop an approach for tackling their challenge.

March 21

Prototyping and Killer Experiment

Teams will meet with MEDIC to prototype and test their concept.

April 27

Pitch Day

Teams will present their solutions at Pitch Day. Top ideas have the potential to be carried on as MEDIC projects.

the challenge

Teams will be formed around one of two global health problems. When you sign-up, you will be asked to indicate which challenge you would like to work on.

#1: Clinic-in-a-Box Challenge

 

An integrated, easy to operate, affordable, and solar-powered suite of medical devices specifically for maternal, child and primary care in low resource settings. Currently, building a reasonably equipped clinic costs more than $100,000. In addition, essential devices are often difficult to install, complicated to use, and expensive to maintain. A suite of the key 10-15 devices that are designed for ease of installation and use (e.g., a ‘clinic-in-a-box’) and collectively cost $10,000 or less can serve as a building block for expanding healthcare in rural areas. Integration needs to occur with respect to power supply and management, patient data, diagnostics, and communication. Potential devices include: diagnostics for critical maternal conditions (malnutrition, anemia, malaria, HIV, syphilis, hypertensive disorders); sterilizers; ultrasound; devices to care for preterm or low birthweight infants (continuous positive airway pressure or CPAP, warmers if skin-to-skin warming is not possible, phototherapy); medical refrigeration; and ICT devices or interfaces for tracking patient data and coordinating care.


The Challenge:
  1. Choose 1 key device for maternal, infant, or primary care.

  2. Interview as many key stakeholders as possible that use your device in rural settings to identify key problems with your device.

  3. Brainstorm solutions to these problems.

  4. Prototype and test your solution.

#2: Disease Vector Challenge

 

Weather and climate conditions (temperature, rainfall, humidity, etc.) influence the range and distribution of a variety of key disease vectors, including insects, rodents, and birds.  Climate, land use, and environmental change are altering these patterns, creating additional challenges for disease control in the United States and around the world.  While disease outbreak prediction systems are still in their infancy, existing data sets can be used to generate useful information about disease vectors.  Timely and simple risk information is already provided for other purposes (e.g., rainfall projections for farmers, hurricane watches/warnings for emergency personnel), but similar systems are not yet in place for disease vectors.  If such a system were to be achieved, this information could be used to take preventive steps, pre-position counter-measures, and save lives.


The Challenge:
  1. Choose 1 key disease vector of concern (mosquito, tick, bat, mouse, bird, etc.)

  2. Assess whether the evidence base is sufficient to predict its range and distribution with existing weather/climate data sets.

  3. Select a relevant geographic scale and time scale.

  4. Work with data custodians and end users to develop an app that can deploy simple risk information (e.g., “watch” and “warning”) for that geographic and time scale.

  5. Test and deploy the system.

community partners

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